현재 위치
Home
Designing a Ubiquitous Decision Support Engine for Context Prediction : General Bayesian Network Approach
-
- 발행기관
- 보안공학연구지원센터(IJUNESST) 바로가기
-
- 간행물
- International Journal of u- and e- Service, Science and Technology 바로가기
-
- 통권
- vol.3 no.3 (2010.09)바로가기
-
- 페이지
- pp.25-36
-
- 저자
-
- 언어
- 영어(ENG)
-
- URL
- https://www.earticle.net/Article/A148518
※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.
원문정보
초록
- 영어
- Ubiquitous decision support systems have remained an imaginary and almost useless system for decades since its first introduction in early 1990’. However, it came out of lab into real world as ubiquitous computing became tangible in the form of mobile devices, pervasive mechanisms, and various mobile Internet technologies. Typically, context-aware systems had received acclaims from both researchers and practitioners as an alternative to making ubiquitous systems touch-and-feel electronics to the users. Nevertheless, context-aware systems lack predictive power which is essential for any ubiquitous systems to suggest timely and effective information for users. Poorly predicted information is likely to degrade the ubiquitous systems seriously. In this respect, context prediction mechanism emerges as a reliable vehicle for making ubiquitous systems more sustainable decision support tool for users. Despite the potentials of context prediction mechanism, few reliable mechanisms exist in literature which shows robust performance against changes in user’ contexts. For this reason, we propose a new type of ubiquitous decision support system that is powered by General Bayesian Network (GBN) capable of organizing causal relationships among a set of related variables. Drawing on the GBN’ strengths, this study proposes U-BASE (Ubiquitous Bayesian network-Assisted Support Engine) to suggest more reliable solution for the context prediction tasks. Performance of U-BASE was tested against real contextual data set, garnering very robust results. The practical implications are fully discussed with some future research issues.
목차
Abstract
1. Introduction
2. U-BASE
2.1. Design
2.2. Usage scenario
3. Experiment
3.1. Data and variables
3.2. Structure learning
3.3. Results
4. Discussion
5. Concluding remarks
References
키워드
Context Prediction General Bayesian Network U-BASE저자
간행물 정보
발행기관
-
- 발행기관명
- 보안공학연구지원센터(IJUNESST) [Science & Engineering Research Support Center, Republic of Korea(IJUNESST)]
- 설립연도
- 2006
- 분야
- 공학>컴퓨터학
- 소개
- 1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업
간행물
-
- 간행물명
- International Journal of u- and e- Service, Science and Technology
- 간기
- 격월간
- pISSN
- 2005-4246
- 수록기간
- 2008~2016
- 십진분류
- KDC 505 DDC 605
이 권호 내 다른 논문 / International Journal of u- and e- Service, Science and Technology vol.3 no.3
피인용수 : 0건 (자료제공 : 네이버학술정보)
함께 이용한 논문 이 논문을 다운로드한 분들이 이용한 다른 논문입니다.
출처 : 네이버학술정보
0개의 논문이 장바구니에 담겼습니다.